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In past decades the scientific community has been looking for a reliable first-principles method to predict the electronic structure of solids with high accuracy. Here we present an approach which we call the quasiparticle self-consistent…

Materials Science · Physics 2009-11-11 M. van Schilfgaarde , T. Kotani , S. Faleev

Energy carrier transport and recombination in emerging semiconductors can be directly monitored with optical microscopy, leading to the measurement of the diffusion coefficient (D), a critical property for design of efficient optoelectronic…

Immense interest in quantum computing has prompted development of electronic structure methods that are suitable for quantum hardware. However, the slow pace at which quantum hardware progresses, forces researchers to implement their ideas…

Quantum Physics · Physics 2025-02-26 Ilya G. Ryabinkin , Seyyed Mehdi Hosseini Jenab , Scott N. Genin

An efficient simulation framework is proposed to model collective emission in disordered ensembles of quantum emitters. Using a cumulant expansion approach, the computational complexity scales polynomially as opposed to exponentially with…

Optics · Physics 2025-12-17 Qingyi Zhou , Wenxin Wu , Maryam Zahedian , Zongfu Yu , Jennifer T. Choy

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure…

Cosmology and Nongalactic Astrophysics · Physics 2021-07-21 Maria Han Veiga , Xi Meng , Oleg Y. Gnedin , Nickolay Y. Gnedin , Xun Huan

Ultra-high dimensional longitudinal data are increasingly common and the analysis is challenging both theoretically and methodologically. We offer a new automatic procedure for finding a sparse semivarying coefficient model, which is widely…

Methodology · Statistics 2014-09-24 Ming-Yen Cheng , Toshio Honda , Jialiang Li , Heng Peng

Superconducting flux qubits are a promising candidate for realizing quantum information processing and quantum simulations. Such devices behave like artificial atoms, with the advantage that one can easily tune the "atoms" internal…

Semi-analytical methods, such as rigorous coupled wave analysis, have been pivotal for numerical analysis of photonic structures. In comparison to other methods, they offer much faster computation, especially for structures with constant…

Numerical Analysis · Mathematics 2022-10-03 Ziwei Zhu , Changxi Zheng

The large number of possible structures of metal-organic frameworks (MOFs) and their limitless potential applications has motivated molecular modelers and researchers to develop methods and models to efficiently assess MOF performance. Some…

Materials Science · Physics 2021-10-04 Krishnendu Mukherjee , Alexander W. Dowling , Yamil Colón

In characterization of quantum systems, adapting measurement settings based on data while it is collected can generally outperform in efficiency conventional measurements that are carried out independently of data. The existing methods for…

Quantum Physics · Physics 2016-11-21 Markku P. V. Stenberg , Frank K. Wilhelm

Combined-resolution simulations are an effective way to study molecular properties across a range of length- and time-scales. These simulations can benefit from adaptive boundaries that allow the high-resolution region to adapt (change size…

Computational Physics · Physics 2018-05-09 Jason A. Wagoner , Vijay S. Pande

Q-learning is widely employed for optimizing various large-dimensional networks with unknown system dynamics. Recent advancements include multi-environment mixed Q-learning (MEMQ) algorithms, which utilize multiple independent Q-learning…

Machine Learning · Computer Science 2024-11-14 Talha Bozkus , Tara Javidi , Urbashi Mitra

In this paper, we consider a semiconducting device with an active zone made of a single-layer material. The associated Poisson equation for the electrostatic potential (to be solved in order to perform self-consistent computations) is…

Numerical Analysis · Mathematics 2023-02-01 Clément Jourdana , Paola Pietra

An efficient implementation of the self-consistent GW method in the FlapwMBPT code (https://www.bnl.gov/cmpmsd/flapwmbpt/) is presented. It features the evaluation of polarizability and self-energy which scales linearly with respect to the…

Materials Science · Physics 2020-08-05 Andrey L. Kutepov

We present a method for the numerical analysis of superconducting quantum circuits combining lumped elements, either linear or non-linear (i.e.~Josephson junctions), and distributed coplanar waveguide (CPW) structures. CPW transmission…

Quantum Physics · Physics 2025-12-09 Simona Zaccaria , Antonio Gnudi

In this review, we discuss the use of continuous variable spectroscopy techniques for investigating quantum coherence and light-matter interactions in semiconductor systems with ultrafast dynamics. We focus on multichannel homodyne…

Mesoscale and Nanoscale Physics · Physics 2023-06-05 Carolin Lüders , Franziska Barkhausen , Matthias Pukrop , Elena Rozas , Jan Sperling , Stefan Schumacher , Marc Aßmann

The presence of disorder in semiconductors can dramatically change their physical properties. Yet, models faithfully accounting for it are still scarce and computationally inefficient. We present a mathematical and computational model able…

Disordered Systems and Neural Networks · Physics 2022-04-13 Jean-Philippe Banon , Pierre Pelletier , Claude Weisbuch , Svitlana Mayboroda , Marcel Filoche

It is well known that the classical energetically consistent micropolar model has limits in simulating the frequency band structure of packed granular materials (see Merkel et al., 2011). It is here shown that if a standard continualization…

Soft Condensed Matter · Physics 2021-04-27 Andrea Bacigalupo , Luigi Gambarotta

The performance of adaptive optics systems employing sodium laser guide stars can be improved by continuously monitoring the vertical density structure of mesospheric sodium along the line of sight. We demonstrate that sodium density…

Instrumentation and Methods for Astrophysics · Physics 2020-04-01 Joschua A. Hellemeier , Domenico Bonaccini Calia , Paul Hickson , Angel Otarola , Thomas Pfrommer

Autoencoding is a popular method in representation learning. Conventional autoencoders employ symmetric encoding-decoding procedures and a simple Euclidean latent space to detect hidden low-dimensional structures in an unsupervised way.…

Machine Learning · Computer Science 2024-10-07 Stefan C. Schonsheck , Scott Mahan , Timo Klock , Alexander Cloninger , Rongjie Lai
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